Do you compute? Fusing Engineering with Neurobiology to Model the Brain

Our brains excel at all kinds of things, but when neurobiologists and psychobiologists try to reverse engineer certain brain functions in order to produce a machine or system that might mimic some of the brain’s extraordinary abilities, more often than not they fail (or at least engineer something that isn’t half so elegant).

Now, researchers funded by Dr. Harold Hawkins (Program Officer in ONR’s Cognitive and Neural Sciences Division) think they’re on to something. By fusing engineering techniques with neurobiology, they’ve been able to model mammalian brain function using biologically realistic, highly detailed models of individual brain neurons and their assemblies. They are learning how the architecture and physiological properties of cells in the brain (the primary visual cortex) integrate visual cues for target recognition. In other words… how the brain computes.

“Right now we’re building a cellular-level model of a small piece of visual cortex,” says Dr. Leif Finkel, head of the University of Pennsylvania’s Neuroengineering Research Lab. “It’s a very detailed computer simulation which reflects with some accuracy at least the basic operations of real neurons.” His colleague, Kwabena Boahen, is building VLSI computer chips that reproduce cortical wiring and many of the properties of the cells. “He has a chip that accurately models the retina and produces output spikes that closely match real retinae. We hope someday that these can be used as retinal implants.”

“We’ve asked them to take a computational approach to neuroscience,” says Hawkins. “They’re looking at object-recognition systems that mimic the brain's ability to find patterns in highly cluttered visual scenes by integrating information derived from bottom-up, top-down and horizontal connections among neurons in the primary visual cortex. It’s precisely what the Defense Department is interested in currently, and for obvious reasons… can we build systems that can instantly pick out an individual face in a crowd? Or parse a visual scene into its many parts? The goal is to use engineering analysis to discern the principles of neural function, and then to use these principles in the design of neuromorphic systems. Taken another step, we could use this same principle to exploit motion information for target tracking in noise and clutter.”

Finkel’s team works closely with physiologists, and there's a lot of going back and forth between the computer models and the real brains. “It's quite an exciting time in the field, with a real sense of progress — Harold’s been incredibly far-sighted about picking up on what's we’re doing and applying it to what the Defense Department might find useful.”

By making models of the visual cortex using brain recordings, by putting neural networks on computer chips, and by building mathematical models, these researchers are, in a sense, "reverse engineering" the brain…developing hardware and software systems that will have a similar ability to solve computationally difficult problems.

Precisely the stuff our real brains excel at without even thinking about it.